Multi-Objective Approach to Determining Gender-Equitable Energy Access in Off-Grid Communities

Across the Global South, energy inequity disproportionately affects women in off-grid communities. However, existing optimisation models for rural electrification rarely incorporate explicit gender constraints. This study develops and validates a multi-objective optimisation framework for balancing environmental sustainability, economic viability, and gender equity in energy access. The model’s objective functions are environmental impact, unsatisfied energy demand, total system cost, and gender inequality. Optimal values for these objectives were generated based on allocation of energy across solar PV, generators, and firewood sources. The Non-dominated Sorting Genetic Algorithm II (NSGA II), particle swarm optimisation (PSO), and a hybrid NSGA-PSO II approach were used to solve the developed model. A remote Nigerian community (Olooji) with 600 households and a population of 7000, classified as Tier 1 energy consumers, was used as a case study. The hybrid NSGA-PSO II method demonstrated superior performance. It achieved the lowest fitness value (4,461,024) by combining the exploration capabilities of NSGA II with the Pareto-optimal convergence strengths of PSO. Over the 25-year planning horizon, the model projects solar energy share to increase from 19.05% to 47.79%, firewood to decrease from 61.90% to 35.45%, and generator share to increase from 14.3% to 14.7%. The community’s energy demand coverage improves from 95.24% to 97.92%. The community maintains a stable male-to-female energy consumption ratio of approximately 1.18:1, while the energy equity gap decreases from 0.2000 to 0.0800 kWh/person/quarter over the planning period. Results demonstrate that the hybrid NSGA-PSO II effectively manages the complexity of multi-objective energy distribution while promoting energy equity and environmental sustainability in rural electrification.